@inproceedings{89a8d63a6b834b6288a6871c51809b8c,
title = "A novel knowledge extraction framework for resumes based on text classifier",
abstract = "In the information age, there are plenty of resume data in the internet. Several previous research have been proposed to extract facts from resumes, however, they mainly rely on large amounts of labeled data and the text format information, which made them limited by human efforts and the file format. In this paper, we propose a novel framework, not depending on the file format, to extract knowledge about the person for building a structured resume repository. The proposed framework includes two major processes: the first is to segment text into semistructured data with some text pretreatment operations. The second is to further extract knowledge from the semi-structured data with text classifier. The experiments on the real dataset demonstrate the improvement when compared to previous researches.",
keywords = "Knowledge Extraction, Resume fact extraction, Text classifier",
author = "Jie Chen and Zhendong Niu and Hongping Fu",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 16th International Conference on Web-Age Information Management, WAIM 2015 ; Conference date: 08-06-2015 Through 10-06-2015",
year = "2015",
doi = "10.1007/978-3-319-21042-1\_58",
language = "英语",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "540--543",
editor = "Yizhou Sun and Jian Li",
booktitle = "Web-Age Information Management - 16th International Conference, WAIM 2015, Proceedings",
address = "德国",
}